Modeling Tumor Phenotypic Heterogeneity with Multi-Strategy Evolutionary Games

Cancer represents a dynamic and evolving ecosystem driven by complex interactions among genetically and phenotypically diverse cell populations. Within the tumor microenvironment, cells engage in both competitive and cooperative behaviors that determine their collective evolutionary fate. To capture these dynamics, we employ evolutionary game theory to investigate the coexistence and adaptation of four representative tumor phenotypes: proliferative (P), invasive (I), resistant (R), and cooperative (C). Using a four-strategy evolutionary game-theoretic framework, we show that explicitly including a cooperative phenotype qualitatively expands the range of polymorphic and noise-sustained coexistence regimes observed in the model, enabling coexistence regimes that cannot arise in reduced three-strategy models. Numerical simulations reveal that frequency-dependent selection promotes stable polymorphisms or oscillatory coexistence among phenotypes, explaining persistent intratumoral heterogeneity. Incorporating stochastic replicator equations further demonstrates that random fluctuations can sustain rare phenotypes, induce transient dominance shifts, and generate noise-driven evolutionary transitions. To explore environmental modulation, we extend the model to analyze tumor evolution under acidic microenvironmental conditions and under pH-buffered therapeutic interventions. Acidity enhances the fitness of invasive and resistant cells, driving the system toward aggressive, therapy-tolerant equilibria. In contrast, buffering restores cooperative and proliferative dominance, illustrating that ecological control of the tumor microenvironment can redirect evolutionary trajectories. Collectively, this work unifies deterministic and stochastic evolutionary game theory approaches to show how tumor heterogeneity arises from eco-evolutionary feedbacks, stochastic fluctuations, and environmental pressures. The results suggest that evolution-informed, microenvironment-modulating interventions may influence selective pressures in ways that favor less aggressive evolutionary outcomes, providing a conceptual basis for adaptive therapeutic strategies.